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Updated: May 28, 2025

Automated, High-resolution Mobile Collection System for the Nitrogen Isotopic Analysis of NOx
Published on: December 20, 2016
Refining δ15N isotopic fingerprints of local NOx for accurate source identification of nitrate in PM2.5
Hao Xiao1, Qinkai Li2, Shiyuan Ding3
1School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China; Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China.
Abstract:
Stable nitrogen isotopic composition (δ15N) has proven to be a valuable tool for identifying sources of nitrates (NO3-) in PM2.5. However, the absence of a systematic study on the δ15N values of domestic NOx sources hinders accurate identification of NO3- sources in China. Here, we systematically determined and refined δ15N values for six categories of NOx sources in Tianjin using an active sampling method. Moreover, the δ15N values of NO3- in PM2.5 were measured during pre-heating, mid-heating and late-heating periods, which are the most heavily polluted in Tianjin. The results indicate that the isotopic fingerprints of the six types of NOx sources in Tianjin are indicative of the regional characteristics of China, particularly the North China Plain. The Bayesian isotope mixing (MixSIAR) model demonstrated that coal combustion, biomass burning, and vehicle exhaust collectively contributed more than 60 %, dominating the sources of NO3- during sampling periods in Tianjin. However, failure to consider the isotopic signatures of local NOx sources could result in an overestimation of the contribution from natural gas combustion. Additionally, the absence of industrial sources, an uncharacterized source in previous studies, may directly result in the contribution fraction of other sources being overestimated by the model more than 10 %. Notably, as the number of sources input to the model increased, the contribution of various NOx sources was becoming more stable, and the inter-influence between various sources significantly reduced. This study demonstrated that the refined isotopic fingerprint in China could more effectively distinguish source of NO3-, thereby providing valuable insights for controlling NO3- pollution.
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